Established work
Process monitoring
Public work around monitoring signals, anomaly review, and inspection-aware evidence boundaries.
Proof
A public map of the work that can be referenced safely: professional context, established LMD/DED work, public frameworks, tools, research maps, GitHub artifacts, and profile links.
Public category
Industrial AI & Decision Systems
Primary promise
AI for Laser Metal Deposition decisions you can verify.
Established proof
AI for LMD/DED at Exafuse
Boundary
Public-safe technical material only
Established work
The public proof layer is specific: AI for Laser Metal Deposition and Directed Energy Deposition at Exafuse.
Established work
Public work around monitoring signals, anomaly review, and inspection-aware evidence boundaries.
Established work
Vision and signal interpretation for LMD/DED process understanding.
Established work
Public profile context around robotic DED/LMD systems and toolpath workflows.
Established work
Repairability screening, RFQ structure, cladding, machining allowance, and inspection planning.
Established work
Schemas, prompts, decision rules, and missing-information checks for LMD requests.
Public proof items
These items link to Exafuse for canonical case or service context. Manish Sharma Lab uses them only to explain monitoring, repairability, evidence, RFQ, and decision-system relevance.
CS15
Public Exafuse proof context
Migration-gated link
Large structural LMD is a CAD-to-production system problem: manufacturability review, path planning, parameter development, monitoring, independent validation, and final inspection.
This is the strongest public anchor for AI-assisted process understanding without replacing inspection evidence.
Decision pattern extracted
Large-scale LMD requires evidence planning, monitoring context, and an inspection boundary.
This is a pattern, not a transfer of feasibility.
CS01
Public Exafuse proof context
Migration-gated link
A credible hammer repair is not one hardness number. It requires surface preparation, crack context, layer strategy, finishing, bond quality, and release evidence.
This maps directly to the LMD Repairability Index and the Quality Evidence Ladder.
Decision pattern extracted
Local repair needs material, damage depth, machining route, and inspection plan.
This is a pattern, not a transfer of feasibility.
CS10
Public Exafuse proof context
Migration-gated link
Repair value often comes from a local failure with a large downtime risk. The damaged material must be removed before rebuilding, not hidden below new deposition.
This is a clean RFQ-intelligence example: damage boundary, lead time, machining route, and inspection context decide the recommendation.
Decision pattern extracted
Repair/RFQ quality depends on complete facts, downtime context, and service context.
This is a pattern, not a transfer of feasibility.
CS13
Public Exafuse proof context
Migration-gated link
LMD can combine geometry creation and functional surface strategy when material compatibility, coating duty, finishing, and validation are planned together.
This supports build-and-coat logic: geometry and surface function should be evaluated as one workflow.
Decision pattern extracted
Build-and-coat routes need geometry, surface function, material, finishing, and validation.
This is a pattern, not a transfer of feasibility.
Public framework
Working tool
Public evidence
Public artifact
Public Exafuse context
Public profile links
Identity path